 Welcome to this third, this is the third online workshop from the social data in the third sector series looking at skills, tools and evidence. My name is Patti Doran and I work for the UK Data Service. I'll turn on my webcam so you can see me. Hello, it's nice to see you. Well, it's nice to know you're there at least. And so today in this third workshop we're going to talk about telling a story with data. And just to give you an overview of what we're covering, I'm going to give a quick introduction. Then I'm going to give a sort of a slideshow presentation looking at telling a story with data. We're going to have a quick quiz just to test that how you understood the presentation. And then I'm going to give a demonstration of how we find and explore data using the UK Data Service website and tools. Then I'm going to give you an activity to do on your own time, which we'll take about 10 or hopefully 15 minutes you'll have for that. And then we'll have some feedback from the activity and finish with discussion and questions. So just quickly to give an overview. The UK Data Service is funded by the Economic and Social Research Council. And it's a single point of access for a wide range of secondary data. But as well as accessing the data, we also run support services. We have online training. We have training guides and videos all online. So there's a lot of support available. And I work for the user support and training team that delivers that support and training. This workshop objective is all about trying to promote our resources to third sector users. So we want to increase understanding within the sector of how data can be used within a variety of ways and support your services. And we want to support you to access that data and be able to use it. And I think by doing that, we'll be able to help you produce the evidence and enhance the service that you provide. So specifically, we're looking, I think it's a good match using our data with the third sector, because lots of the organisations in the charity or voluntary sector are working with groups whose social data is collected about. So you might be working to improve outcomes for marginalised groups or reducing inequalities and providing a range of support to those most in need. And we're aware that the funding for lots of the services, lots of the charity sector relies on continual funding. And to get the funding you need to demonstrate your impact. And providing qualitative data to support your work can help do that. And so the data that we hold at the UK Data Service can help provide the context and demonstrate where services are most needed. And just to reiterate, I know some of you have heard this before, but we know that within the third sector, there's a whole range of organisations. So it's quite hard to sort of provide training that's specific to you. So hopefully you'll get an overview stay of what's available and we'll be able to follow up with some of the resources that we have to help your work further. So just to say that in the UK Data Service, we hold different sorts of data with aggregate data, a particular census data that we covered in the first workshop, microdata from surveys and other sources, and we also have qualitative data. But today we're looking at microdata, specifically the UK surveys. So we're going to talk about how you can tell a story with data. So why use social survey data first? So it's very large datasets and the findings from any analysis, if you use the big robust datasets, are generalizable to the population. So it provides quantifiable evidence to help explain social problems and it provides context and justifies the needs for services. And I just wanted to point out as well that it can be used alongside other evidence from project delivery. And I'm going to give two examples now of how social survey data has been used in these ways. So first of all, this is me from another life it feels like, before I thought that going into research was a good career move. So I used to work for Manchester City Council and I was funded for many years, several years, by Macmillan Cancer Support to develop and run a information support service through Manchester Libraries. So Macmillan funded me to do my masters and I wanted to investigate the influence of emotional support on the quality of life of older cancer survivors. And so the focus of my thesis kind of developed on some a campaign that Macmillan was running at the time called the age-old excuse and they were exploring this trend that was seen sort of in the health data of the under treatment of older cancer patients. So what that graph is sort of demonstrating is that there's kind of across the different cancer types, there's a similar level of treatment and then treatment begins to drop off at the age of 60 for some cancers and more significantly around 70 to 79 for other cancers. And by the time you get to 80, you know, your chances of getting certain treatments are quite low compared to those in the younger age groups. Of course there's many reasons for that, but one of my theories was that having support network around you and people to advocate for you perhaps would influence how much treatment you got. And so I use data from the National Cancer Patient Experience Survey which is held by the UK Data Service. This is just a screenshot of the catalog record that we have. And so the Cancer Patient Experience Survey as you'd kind of take from the name is questions people, surveys people about their experience of going through the system and having cancer treatment. And there's questions about what treatment they received. And you can see hopefully on the side here this is the number of cases. So there were 71,000, nearly 72,000 people interviewed in the survey. So it was a very large data set. And what I looked at is how much treatment different people had. And I looked across all cancer types. And so it was a bit of a crude measure, but I was looking at how much treatment people had. So whether they had no treatment, one treatment, two treatments or three treatments. So that could be one treatment of chemotherapy and a treatment of radiotherapy or surgery or, you know, two rounds of chemotherapy or whatever it was. And so I just compared whether people had no treatment to three and just looked at the trends. The first graph, the one on the left, is just the count. So you can see that most people received either two treatments or one treatment. And much fewer people received no treatment or three treatments. That's less common for those occurrences. So for example, it would be very common for people to have surgery followed by chemotherapy or surgery followed by radiotherapy. But to look at it more clearly, to look at any sort of inequality across age, I changed it to a percentage. So I was looking at out of all the people who might not receive no treatment or three treatments or one or two, what percentage was in each age bracket or wasn't actually an age bracket, it was at each specific age. So that's how I got the continuous variable and the trend that goes across. And when you look at the percentage and you're looking at all the different the categories with different numbers of treatment, you can very clearly see that no treatment was much more common in the older age groups. And it was much less common in the younger age groups. And in fact, the trend was reduced to this blue line is the three treatments, two treatments, one treatment, no. And it's the opposite order in the older age. So that was my finding that supported the research that McMillan was doing or the campaign that McMillan was running about age and age inequalities with treatment. So that's one example. The next example I'm taking from a blog post that I mentioned last week. So this is some work that was being promoted by Morgan Vine from National, it was on the National Voices blog page and she works for Independent Age and I'd put out a report looking at older people and looking at their experiences and particularly looking at sort of minority groups across older people to see what their experiences were and how they differed. And in this piece of work that they did, it was actually used a mixed methods approach. So first of all they did a scoping review so they kind of collected information from literature about what they already knew about the topic. Then they conducted in-depth qualitative interviews with I think there were about 45 older people. And then they carried out some analysis of quantitative survey data. And they used Understanding Society, which is one of our key datasets. It's actually a longitudinal study so it follows the same households across time. But it can also be used for a snapshot of the population to find out what their experiences are. And I quite like the way that they presented their findings. So this is just sort of one section of it. They had about six or eight different groups of older people. But here we can see people with physical health conditions and people with mental health conditions. And they had on the left what they found from their scoping review, what they knew from the literature, the problems that were evident. And then they had like quotes from the people they interviewed and what they were highlighting as issues. And they put that alongside some of the statistics that they're drawing out from the Understanding Society research from the study. So they were adding the quantitative findings to their qualitative research and what they generally knew from the literature to add a bit more robustness to the report that they were producing. So that was one way of using the quantitative data to tell a story about the problem that they knew already existed. And they had done further research into through the interviews. So they just used the data to sort of back up what they already knew. And by adding these nice graphs and figures it kind of quantifies the problem a bit more and makes it a lot more tangible. And I just wanted to point out at this point as well that we have a blog, a data impact blog at the UK Data Service. And here you'll find other examples of how people have used data to tell stories and data to address a problem that they see. And I'd encourage you to have a look. And I'd also encourage you, if you are using any of our data, to get in touch. If you'd like to write about it and write what you found. And we can support you to do that if you'd like. But we're always interested in knowing how people use our data and what stories they are telling. So I just wanted to signpost you there as well. Second half of this presentation, I just wanted to talk about how you go about finding data to tell your story. So there's different ways of finding data on the UK Data Service website. You can use the data catalogue which you'll find on the main homepage of our site. You can search for datasets. And when you put the search term in, it will search either for a word in the dataset title or for keywords or from the abstract. But so it will be broad connections to the topic. You can also search, if you click on Get Data, which is one of the tabs at the top, it will bring you to this page. And from there, you can click to Key Data or Data by Theme. And you can use those ways to start to look at what sort of survey data might be available for your needs. To reiterate, we hold a lot of data. I think there's like 7,000 datasets. So it can be a bit of a process to find the data and to know which data is going to provide a robust sort of example for your needs. And so the key data we have is all data that you know will be generalizable to the wider population. We hold data from the big government surveys, from big research centers. But we also hold data from individual research projects. If you had data that you wanted to securely store, you could store your data with us. So we're a safe repository for any social data or even some data that's not specifically social survey data. And so not all our data is going to be the same size and quality as each other. It's up to the individual depositors to deposit with us what they see fit. So by going to our key data sets, you know that you're looking at data that is of a certain standard. It's about the whole of the UK generally. If you're looking at the UK survey data, and it will be generalizable to the population as a whole. So going to the key data is a good way to find data that you know you can rely on for that sort of evidence. And the same is with the data by theme, but it's just categorized in different ways. So it's got different topics that you can start to narrow down where you're looking for for your data sets. And then somewhere else where I'd suggest that you look for data, which I touched on last week, is the variable in question back. And we're going to explore that a bit more in our activity in a bit. The other way to look for data is to open it up and just have a look at the data and see if you think it's telling you what what you'd like to see. So one way of doing that is to explore by Nestar, which is an online tool we have, where lots of our data sets are loaded into. We did a bit of exploring of that last week in workshop two. We'll have a very brief look at that again today. So I'd encourage you to use that to look at the data. But some advice that I was given not long after I started at the UK Data Service was just to open it up and have a look. So there's nothing stopping you downloading full data sets from the UK Data Service when you're just exploring and you're just trying to get an idea of what's out there. I used to sort of think that every time I downloaded data, I sort of had to be using it because it was such a, you know, it's kind of a safeguarded resource and I kind of thought I'm only going to download it if I really need it. Part of that was because when you opened it, it sometimes seemed so big and overwhelming as well. I kind of didn't want to go there unless I sort of needed to. But I was encouraged to do it more and now I do. So downloading data sets is something that I do on a daily basis just to have a look. I mean, that is sort of my job as well. So that's a bit of a given, I guess. But I do encourage you to download data sets and have a look. So there's a screenshot here from R where I've just opened up the crime survey for England and Wales. This is just teaching open access data set that you see here. But once you have the full data set open, you can kind of search through it for questions that you liked and automatically start to do some descriptive statistics just to see what's available. You can do some of that in Nestar as well. But if you have the whole data set open, some ways you're going straight to the questions that you're looking for. And it's a one way of exploring and finding the data that you want. And so I just wanted to touch on a couple of other things, other points that I made last week just to reiterate that it's really important to make sense of your data so that you look at the documentation. So you need to know what information was collected, where it came from, when and where it was collected, how the data's been changed before it's been archived. And we have the whole set of user guides, questionnaires and interview schedules attached to every data set. So you can look at those in order to help make sense of your data before you do delve too far into it. And also as I said last week, it's not a linear process always when you're trying to find data. It's iterative. You have to go back and forth. So you might have your problem that you're trying to address and you might get open up some data that you think will be perfect and you find it doesn't actually have all the questions you want. So you kind of go back and forth and explore different data sets in different ways. So you need to set aside some time to explore different data sets, explore different questions, explore different ways of finding the right survey data to answer your questions. So that's where we're going to leave the presentation for now. So I'm just going to ask you a couple of questions just to check that they're all made sense. So there'll be a couple more polls that come up on your screen. And if you just answer those for me, we'll see how we go. So the first one, what's one of the reasons why you might use quantitative social data? And most of you said, as I was trying to emphasize, because it helps provide context. But everyone does like statistics as well. That's a very genuine point to make as well. That kind of has just been a bit cheeky when I put that in there. But I think particularly funders, like some funders like statistics or like some statistics, and no one selected because the government funders spend lots of money collecting it, which is true. But it's not really the main reason to do it is because it does provide such excellent context to what we're doing. So that's great. We'll move on to the next question. Using the UK data service website, there are several ways to find data. True or false? That's right. It's true. There's lots of different ways to find data. In some ways, it's a bit unfortunate. It's not like the diagram I showed before. It's not a linear process to go through our website and find the data that you're looking for. You might want to try different ways. And eventually it will all sort of build up into a direct path, perhaps, and you'll find the data that you're looking for. So I think there's one more question now. So finding the right data is a linear process, an iterative process, or all about luck. Again, these questions aren't really about right and wrong answers. It's mainly to make you sort of think about the process. So I generally would say it's an iterative process. I mean, it could be seen as a linear process, but it goes back and forth and around, but eventually you get the straight line. Or it could be all about luck sometimes if you find the right data. So yeah, so it's just to emphasize that it is a process. So now I'm going to show you a little demonstration of the website and how we might go about finding data. I'm just going to turn off my webcam so that it gives you a bit more space. Please do say, I should have mentioned earlier. In fact, someone got a question already. We do have a question box if you have any questions as you go along. I will answer them at the end of the discussion, but feel free to put them down as you think about them. So the question box is in the go-to webinar control panel. There is also the option to raise your hand. I've got someone with their hand up. If perhaps you want to write your question in the question box, and either myself or Ellie might answer the question as we go along. So just please do use that question box and we'll return to that at the end. But for now, we're going to have a look at the website. So hopefully, I'll just double check that you can see my screen. I think you can. So this is the UK Data Service website. And as I mentioned on the homepage, there is a search bar. So that's to search the data catalog. So as an example, we can imagine that we were interested in computer use. We're interested in how many households perhaps have access to computers or are able to use computers. And we want to provide some context in that. So we want to find out about computer usage. So we put computer usage into our data catalog and see what comes up. So as I mentioned with the data catalog, it's searching survey titles. It will also be searching keywords and it will also be searching abstracts. So you can see the first things that come up are things that have computers in the title. But perhaps it's not so helpful to find out about the computer survey from 1970. That's not exactly what we're after. So we might refine the dates here on the left hand side and say we're interested in things that are more from, at least maybe should we say that last 10 years. So since 2010, and we'll refine that date. And so then we've got different things coming up. Some things that look a bit sort of interesting. So there's not many at all really that are coming up. Now I've only got five results. So maybe something isn't quite right about what I'm searching. And it's not quite what I'm after. So I'm going to go a bit older that some of this data catalog should have quite a lot around computer usage you would have thought. So I'm kind of thinking something I'm doing is going wrong. So the things that you can do to help focus your your searching is use these things on the side because some of these studies I would say a qualitative studies because we're searching the whole catalog which includes qualitative as well as quantitative studies. And perhaps we've been a bit too specific in our search terms. But first of all I want to take out any qualitative studies. In fact, I'm just interested in UK survey data. And you can see there's only one there. And this is perceptions of electricity use at home and in the workplace. And that's from Nottingham University. So that's not one of our big key datasets. That's a single study that's been completed by someone from Nottingham University. So that's a bit unusual. So you kind of think well I'm not getting to where I want to with the data catalog. And that couldn't part be because it's only searching the titles. And not many titles are going to have or abstracts or keywords are going to have things known about computer usage. So I'm going to try a different route. So I'm going to go up here to get data. And see what I can find. So from get data you can still browse the catalog. But I'm going to have a look at the key datasets and see what I can find in terms of things that I think might, servers that I think might hold the information I'm looking for. And so I start to scroll down the list and or maybe community life survey. Maybe, maybe not. Family expenditure survey maybe. Not quite sure. General lifestyle survey. That might be good. I might click on that and explore that one. But you can see there's quite a long list of surveys that we call our key surveys. So these are all surveys that we know it tells you up the top here. All surveys that can be used to inform policy. And that they can, from the analysis of it, you can compare populations from one point of time. So there's lots of surveys there. So that's kind of just mind boggling a bit, blowing my mind. So it's not helping me focus this down. So I'm going to look at the themes. And so from the themes, we've got big themes that they group the key datasets by. And so if I scroll down here, there's a theme for information and communication. And that might be a, I'll find more information. So I'm going to have a look down there. And so this is all the key data that we've got about information that tells us about information and communication. And you've got the British cohort study, which is a big longitudinal study, the British social attitudes survey. And that sounds like it might be interesting. And you can see this table here. And you can see this table here is refined by study name, the coverage and the topics. And here the topic, it actually says internet usage. And I'm like, oh, that's probably where I was going wrong. You know, I still think of computers and internet sort of interchangeably when perhaps that was the problem I should have been looking for internet usage as opposed to computer usage. Depending on my topic, on my thinking, am I really interested in how many people have computers in their homes? Or is that less relevant now that people have access to the internet using their phones? My sister likes to tell me that your phone is a computer. It's certainly more powerful than the Amiga that we had in our family home as a child. So thinking, all right, so this is what I'm looking for now. I'm looking for internet. So this is helping me focus my direction. It's helping me focus on what I want to look for. This one does have computer usage, which is interesting. That's growing up in Scotland. That's a longitudinal study following children who grow up. So in television viewing, lots of these studies are now bringing in things like tablet use and just any sort of device time as well. So, but I think it's important to note that you have to be quite careful about your use of terms and the terminology that you use. So bearing that in mind, I'm going to go back to this get data tab at the top and I'm going to look at this box here, which is the variable in question bank. So this has a whole repository of survey questions. And so it asks us, so we can search in here for any questions about internet use, I shall put and see what comes up. And so now we're looking for exact questions around internet use. And you can see that also we've got questions here saying that secondary activity, this doesn't make a lot of sense to me right at the moment. So if we maybe view the responses and it tells us, I see, so it's telling us this is the time you survey and it's telling you how you use your time. And so internet must be one of the uses of people's times. So like, okay, that's making a bit more sense. So you might be able to find something from a time use survey. But there's a lot here and they all seem to be the same, they all seem to be from the time you survey, time you survey. So is there a different way of looking at this? And so you can look at it from a series point of view. So because every time the question is asked in the time you survey, it will come up as a different result from the variable question bank. And it's the same with the catalogue. So you can either look at it per individual survey, or you can look at it from the whole series of that survey. So I'm going to click on this first one and see what happens. The opinion and lifestyle survey and refine that. And now we're getting into questions that I'm a bit more interested in. Do you not use the internet? Reasons given for not using the internet. So we can have a look at some of these and see what the answers are. And so you can see the poor opinion of the internet. That's all missing from that one. So that's quite interesting. But it's still giving you an example of a survey which asks a question about the internet, about the topic that you're interested in. So this is a good way to begin to find out what sort of questions are asked and where you might find them, where you might find the answers. And you can continue to refine your results by using the different boxes on the right. So you're going to change this one to internet usage and see if that comes up. So reasons to get broadband. And again, why did you upgrade to broadband? So different answers are coming up. So you have to keep trying and seeing different ways that questions are asked and different surveys that ask the questions. And eventually you'll find something that you're looking for. But it can be a bit of an investigative process. So this one is taking me to the omnibus survey from 2005. And so I might view that catalogue record and see what happens. So this is telling me about the omnibus survey. And I think you might even see that in the key data. I don't know what this omnibus survey is. So you scroll down, you have a look at the catalogue and you see what you can find down here is the abstract. And it tells you that the opinions and lifestyle survey formerly known as the omnibus or the ONS opinion survey. And so now things are beginning to link together because I think we saw earlier under things that opinions and lifestyle survey was one of the ones that asked questions about information and communication. So we're beginning to get warmer we think. Things are linking together. So I'm just going to go back to that page that came from the variable in question bank. Because this can be, this is quite an interesting point to move from. And so I'm going to look now to see what happens when I view response percentages. I'm just going to open that in a new tab by right clicking on that. So I can come back to this page. And if I want to search the variable in question bank again, I'm going to go up to this page. Oh, internal server error. That's not good. That was taking me to Nesta though. We can see up here I was in Nesta. So normally that would link right through to Nesta. I hope it's not down because we're going to all use it in a bit. So I'm going to pick earlier survey and see if I can get through to Nesta. So I'm going to look at date here. I want just to look for when it might be that that data set was actually too old to look in to Nesta. So yeah, 2010 we'll try and refine that. And so now we're up to the opinions and lifestyle survey and we can see that that actually had internet access module in 2014. So that's interesting. We can explore that and we'll find out lots of information potentially about internet use. So that's more like what we're after. This box here, you can see expand to view the responses. And so we've got the question, how did you pay for the goods or services you ordered over the internet in the last 12 months? And straight away by dropping down this box, you can actually see the answers to that question. So it's interesting to know what the answer options were, but also what the actual responses were. So provided by credit or debit card over the internet's prepaid account. So you're like, well, that is quite interesting. Maybe I will look into this one a bit more. And you've got the answers there. But again, it would be much more helpful to look at that as a percentage of, we can't even quite see here how many people were in the survey. So these exact numbers aren't giving us really the detail that we want. So I'm going to try again to look at the percentages. And here we go. This is more what we're after. So now we're in Nesta, and it's linked us straight through to that survey, the opinions and lifestyle survey in Nesta. So this is an online tool to explore the survey data. And you can see we've gone straight through to this question, how do you pay for the goods and services you ordered? And now we've got it in a little bit of a, we've got the numbers still, but we've also got it graphically in a little graph. And we've got the percentages. So that we know that most people who pay for goods and services over the internet pay for them with a credit or debit card. That's 85%. So that's most of them. But what I think is quite helpful about linking through to Nesta in this way is that it shows you all the other questions that were asked around the same things in the survey. So you can see we've linked through here to the internet access module questions. So now we have all the questions that were asked around internet access. So you can scroll up and down this and say, do you have access to the internet at home? And that was one of the things I was interested in. So we've got, yes, for 83.6%. And you can see now the number of cases as well. That was 3000 cases. So now we're finally beginning to understand or find the answers to some of the questions that we're after. You can see this from 2014, this data. But we know that the opinions and lifestyle surveys repeated frequently. So we'll be able to find most more up to date data as well if we want to. And we've got all here all the different reasons that people might not have internet at the home. When did you last use the internet? That might be interesting. Most people are saying within the last three months, but you've still got 10% of people saying they've never used it, which is quite a reasonable proportion. Your household is internet, but you have never used it. Is that right? So we've got all sorts of questions here. So you can scroll through just to find the sort of questions that are being asked and the sort of replies. The reason that questions might be repeated like this is in the survey that broken it up so that each response or each variable here is only one answer. It's one category of the question. So this is response one. So you'd have to look into the documentation like I was saying earlier in order to fully understand what some of these questions are asking and to make sure that you're understanding the context of how the question was asked correctly. So that is the way you'd go about exploring the data using Nesta. Oh, and I didn't open in a new tab here. So I can't go straight back to the UK data service website without scrolling through all the tabs that I've picked through, which is why I said just earlier that you open it up in a new tab. But just a reminder, so we got here from the variable in question bank, searching the internet, and we got to the variable in question bank from get data. So that was how we linked through that process and explored for that question. And the only other thing I was briefly going to show you was the other way if we went back then to the UK data service website, and then we decided that we were interested in the opinions and lifestyle survey because they had all those questions that we wanted. This is what I was saying earlier about lots that every instance of the survey comes up when you do a catalogue search. And it's not necessarily in chronological order, it might be which surveys are used more often. So the easier way to go to it is to click on this tab here, which is series. And because the opinions and lifestyle survey is one of our key datasets, it has its own series, where all those surveys are linked together. So we can click on the opinions and lifestyle surveys here. It gives you an abstract and you can access the data there. And then from here, this is the most recent ones, that's older ones, the 1990 to 2007. And so that's secure access, these ones. So this middle one is the one we're after, we're after more recent data. So you can drop down from here and see all the different surveys that we can either explore online with Nestar, or we could log in and download a full dataset and explore it with our own computer. And I've just opened up a dataset, an R, again this is the crime survey for England and Wales, but you can open up the data in a software package and then explore it online and start to pull together any sort of descriptive variables that you're particularly interested in. So you can find out the responses to different questions and perhaps start to do some cross tabs and work out how they relate to other questions and start to just really investigate whether or not that survey is a survey that is going to answer the questions that you're looking for. So those are all different ways that you can go about exploring survey data and using the UK data service. And so now we're going to do an activity and you're going to have a go of exploring some of those ways of finding data. This morning you were emailed the handout for this activity, but it should look like this. And if you didn't have it on email yet it is available in the go to webinar control panel under handouts. It's a PDF handout. And if you have trouble using the UK data service website and following the instructions in the handout, I suggest you use alt tab or command tab if you're on a Mac to flip through screens. It's quite an easy way of going back and forth. There's several questions throughout the worksheet and if you just jot down the answers to those we'll do some polls at the end. So if you follow the instructions on that handout you can post any questions or if you need any help in the questions box in the go to webinar control panel and we'll do our best to answer them and to help you through it. That just worked through the exercise in your own time and we'll, as I said, we'll answer some questions at the end and we'll come back together. What's the time now? We'll come back together at three o'clock to answer those questions. So work through the handout, put any questions in the question box and we'll come back together at three p.m. to discuss the answers. Thank you very much. Okay so it's three o'clock so we might come back together now and kind of have a discussion about how you got on with those with that activity. Hopefully you got through it. So if you're all able to come back to the main screen, I'm going to ask first a few questions to see how you got on. So firstly, did you manage to complete the activity or at least get most of the way through it? Looking like most of you did. That's good. All these worksheets will be put up with the recording of the workshop in a couple of days so if you want to go back to it or if you want to suggest to a colleague or something, the PDF will be there with the workshop recording on our system. So that's great. Thank you. So the first question that you came across in the activity, so how many respondents from the British Social Latitude Survey 2016 replied to the variable CC believe with the answer, I don't believe that climate change is taking place. So this is the answer that you could have got from just from looking in the variable in question bank and dropping down the cross there and where it doesn't have the percentages but it does tell you the absolute numbers of people that responded to different questions. And I think most of you have got it there. It was 150. So it looks this is the sort of screenshot which you should have come across when you dropped down this part here. So 314 was I believe that climate change is taking place but not as a result of humans and it was 150 that said I don't believe that climate change is taking place at all. So if we go to the second question, so now we wanted to know what the percentage was. So that meant clicking on the question and drilling down a bit more and linking through to Nestar. So hopefully Nestar worked for you all. So what percentage of respondents was that, that 150? What percentage was that of the total people that filled in the survey? It looks like everybody's pretty much getting this one right. So that's great. So that was the 5.1%. So again from the Nestar page you could see the percentages but you could also see, I didn't put it in the screenshot, but you could also see the total number of respondents. So it was around 3000 respondents. So that 150 represented 5.1%. So we'll go to the next question which was what do people think about climate change? So this was the whole question that we were trying to explore effectively. What attitudes potentially need to change? So to answer this question I was just really looking for you to explore the other questions in Nestar, having a bit of a look to see what else people were asked and what their responses were different things. So I gave you three options of what might have been things that came out from that. So this was a bit more of an exploratory question and you might think that people think something else about climate change, but I sort of just picked out one thing that I thought was interesting from the other questions. So this is me sort of projecting my sort of finding onto this question. So the whole process was just to find out, was just to explore the data. So I think most of you have answered that question now and you've kind of selected the point that I highlighted it, which I thought that it was quite interesting that many people did actually think that planes contributed. I think I put in a slide here. About half people interviewed thought that planes did contribute to climate change. So there was an awareness and acknowledgement that flying was not great for climate change, but then when you looked at the percentage of people that were willing to change their behaviours, there was a strong sort of negative skew going on. Most people were saying that they disagreed. I mean there's a significant portion there, 22% that say they never flies, that's not too bad, but compared to the other categories there, like when we looked at where people prepared to stop driving more, more people were saying agree to that when we're flying, there seemed to be quite a strong resistance to giving that up. So I thought that was kind of interesting. And then there was just one final question. So linking back to the catalogue and having a look at the catalogue page for the British Social Ed Sheets survey and looking at what was the main collection method. Was it a web survey? Was it a face-to-face survey or was it a phone interview? And so when you go to the catalogue page, if you scroll down to the bottom half of the page, you find the methodology. And the methodology, you will see this. And as most of you have said, you can see that it was a face-to-face interview. Just as an aside here, I guess, this is kind of further evidence of how significantly surveys are. Most of these key surveys that we hold are conducted face-to-face in people's homes. So there's a whole group of people out there whose professional occupation is survey interviewers. And they go into people's homes. And these interviews can take generally about an hour, maybe more. And they go into people's homes repeatedly. And for the longitudinal surveys, they go every two years to the same people. Other people are contacted randomly, and they just might get a letter first, and then they get knocked on the door asking to be interviewed. And there's these interviews that give them these quality face-to-face interviews for a substantial period of time. So it's all the status collected in a very robust way. Obviously, a lot of these surveys have been put on hold at the moment. So it's going to be very interesting to see what happens with the data in the coming year or two. Lots of these surveys have moved to web-based or to phone-based. So it's changing, and that change in data collection will have some impact on the answers. So that's an interesting sort of just a side to consider.